Digital solutions for decision support in general practice – a rapid review focused on systems developed for the universal healthcare setting in Denmark

Background Digital health solutions hold the potential for supporting general practitioners in decision-making, and include telemedicine systems, decision support systems, patient apps, wearables, fitness trackers, etc. Aim This review aimed to identify digital solutions developed for, tested, or implemented in general practice to support the decisions of GPs in disease detection and management, using Denmark as an example country of a universal healthcare setting. Methods This study was conducted as a rapid review. The primary search included a database search conducted in Embase and MEDLINE. The supplementary search was conducted in Infomedia and additionally included a snowball search in reference lists and citations of key articles identified in the database search. Titles were screened by two reviewers. Results The review included 15 studies as key articles describing a total of 13 digital solutions for decision support in general practice in Denmark. 1.123 titles were identified through the database search and 240 titles were identified through the supplementary and snowball search. Conclusions The review identified 13 digital solutions for decision support in general practice in a Danish healthcare setting aimed at detection and/or management of cancer, COPD, type 2 diabetes, depression, liver disease or multiple lifestyle-related diseases. Implementation aspects should be reported more transparently in future publications to enable applicability of digital solutions as decision support to aid general practitioners in disease detection and management. Supplementary Information The online version contains supplementary material available at 10.1186/s12875-023-02234-y.


Introduction
Digital health interventions provide new approaches for utilizing health data in the prevention, diagnosis, and management of diseases [1].Digital health covers a wide range of digital solutions such as telemedicine systems, decision support systems, patient apps, wearables and fitness trackers, etc. [2].Digital health interventions can support healthcare providers in disease detection and prevention by providing prompts or alerts for patients at high risk of disease.
In this review, Denmark is used as an example country with universal healthcare coverage, as all citizens have access to needed medical services, which are primarily tax-funded [3].Danish citizens have free access to a general practitioner (GP), who acts as a gatekeeper for referrals to specialist or hospital care [4], and 96% of Danes have contact with their GP over a three-year period [5].Access to care in the secondary healthcare sector is also free, providing that the patient received a referral from their GP, ands GPs are therefore usually the first pointof-contact to the healthcare system [4].GPs are selfemployed, and general practices are funded through contracts with public authorities [4].Practices are usually fairly small, consisting of 2-3 GPs plus nurses and secretaries, serving 1500-1800 patients per GP [4,6].
Danish general practices are overall fully digitized, with patient records and clinical data communication between general practice, hospitals, and pharmacies fully computerized [4].Further, digital consultations are available in general practice [4], and Denmark tops the list in an OECD comparison of European countries in eHealth adoptions [7], which overall suggests that the Danish general practice setting is quite mature in terms of digitization.The gatekeeper role that GPs occupy in the Danish healthcare system makes general practice eligible for implementation of digital health interventions to improve the early detection of patients at risk of diseases in a Danish context [4].
Digital solutions can be implemented into GP software systems as decision support systems to alert GPs of patients at high risk of disease, and aid GP decisions for referrals to diagnostic procedures or treatment initiation at specialists/the hospital.To our knowledge, there is at present no available record of digital decision support systems in general practice in Denmark.Therefore, this rapid review aimed to identify digital solutions developed for, tested, or implemented in general practice to support the decisions of GPs in disease detection and management, using Denmark as an example country of a universal healthcare setting with a fully digitized general practice sector [4,7].Findings from this review may be relevant to other countries with similar digitized universal healthcare systems.

Methods
This study was conducted as a rapid review, and reported according to PRISMA guidelines where applicable [8].The PRISMA checklist was provided in supplementary material 1.

Data sources
The databases Embase, MEDLINE, and Infomedia were included as data sources.

Search strategy
The search was divided into a database search and a supplementary search.The database search was performed in Embase and MEDLINE using a Boolean search strategy.The strategy consisted of three blocks: Denmark (block 1) AND General practice (block 2) AND Digital solutions for decision support (block 3).Each block consisted of keywords that were combined with the operator OR.The block search was conducted using the operator AND between the blocks.Keywords for blocks 1 and 2 were chosen after consultation with a research librarian from the library of the University of Southern Denmark.Further, keywords for block 3 were chosen from validated health app filters [9] and adapted to the current search strategy in collaboration with the research librarian.The search strategies are available in supplementary material 2.
The supplementary search was performed in Infomedia with Danish sources including the Danish Medical Journal and Dagens Medicin.The motivation for the supplementary search was to leave the search strategy open to sources that were not necessarily peer reviewed, but could still describe digital solutions relevant to the aim of this review.Infomedia was searched using the following keywords: digitale løsninger (digital solutions).Grey literature was included in the supplementary search to ensure a broad perspective on the field.
The supplementary search also included a snowball search examining reference lists and citation searches of relevant key articles.
Publication dates were limited to 2010-2022 and searches were limited to English or Danish language.This review differentiates terminologically between studies and articles throughout the presentation of findings.Studies were defined as peer-reviewed scientific studies identified through the database search.Articles were defined as sources identified in the supplementary search which included grey literature such as news articles etc.

Defining decision support
This review defines decision support or aid for GPs as the dissemination of patients' healthcare information to GPs to provide an information base in consultations and patient care, or as the automatic identification of patients at risk of disease.This could, for example, be a digital tool that alerts GPs of high-risk patients, thus informing GP decision-making and possibly enhancing diagnostic accuracy in general practice.To clarify the definition, this review defines digital solutions for decision support as material/tools made available to the GP through electronic software systems and not as analogue material (e.g.on-paper tools).
Figure 1 below depicts how digital decision support could be used in a Danish GP setting.Depicted is the setting of a consultation between a GP and a patient.The basis of any care decision is clinical experience, medical guidelines, symptoms, lab results, medication information etc.Digital decision support contributes to the GP's decision-making by generating a reminder, recommendation, alert etc. which the GP may consider in combination with other clinical information in deciding upon any further action for the patient.The decision rests ultimately with the GP.

Inclusion and exclusion criteria
The inclusion criteria were as follows: • Digital solution e.g.pop-up, app, etc. • Decision support or aid for GPs.• Danish setting.
• General practice setting.
• Peer reviewed (Only applied to database search).
The exclusion criteria were as follows: • Foreign setting (non-Danish).
• Not peer-reviewed (Only applied to database search, grey literature was included in the supplementary search).• Hospital setting or other non-GP settings (e.g.municipal health centers).
If the inclusion or exclusion criteria could not be assessed on abstract alone publications were included for full-text screening.

Risk-of-bias assessment
As this rapid review did not aim to evaluate intervention effects, but only to identify digital solutions developed for or implemented in a Danish general practice setting, a risk-of-bias assessment was deemed unnecessary [10].

Screening process
Two reviewers, Anne Clausen (AC) and Emilie Rosenfeldt Christensen (ERC) dual-screened 20% of titles and abstracts of studies identified through the database search, with conflict resolution.One reviewer (AC) screened the remaining abstracts and the second reviewer (ERC) screened all excluded abstracts and Fig. 1 Example of a digital decision support system in a Danish GP setting resolved any conflicts if needed [11].All articles from the supplementary Infomedia search were dual-screened.The snowball search was conducted independently by both reviewers and findings were discussed until an agreement was reached.

Results
The flow of the screening process is shown in Fig. 2 and described in detail in the following.A total of 1.123 studies were identified through the database search.After removing 194 duplicates, 929 studies were screened on title and abstract.Through the title and abstract screening, 849 studies were excluded based on the criteria outlined above.If the inclusion and exclusion criteria could not be assessed through the title or abstract alone the study was included for full-text screening for further investigation.A total of 80 studies were screened by full text, of which 66 were excluded based on the following: insufficient description of decision support/aid (n = 16), non-Danish setting (n = 14), non-general practice setting (n = 5), decision support/aid not aimed at GPs (n = 19), full text not available (n = 8), and non-peer-reviewed (n = 4).The remaining 14 studies were included in the review as key articles.
The supplementary search in Infomedia identified 234 articles, which were screened on title and first paragraphs.After the assessment of the title and first paragraphs, 227 articles were excluded based on the criteria outlined above except for the criteria of peer review as grey literature was permitted for inclusion.The full text was retrieved and screened for 7 articles, of which 5 were excluded for the following reasons: decision support/aid not aimed at GPs (n = 2) and insufficient description of decision support/aid (n = 3).The 2 remaining articles described solutions that had already been identified through the primary database search.These 2 articles were therefore included only as supplementary sources for the description of the identified digital solutions.
Through snowball search 6 studies were included.After assessment in full text, one of these studies was included in the review as a key article as it described a digital solution not identified by the primary database search, while the remaining 5 were included as supplementary sources.
The 15 key studies described 13 digital solutions for decision support in general practice.The characteristics of the 13 digital solutions are outlined in Table 2. Further elaborations of each digital solution can be found in supplementary material 3.

Knowledge summary
This rapid review identified 15 key studies (Table 1) describing 13 digital solutions (Table 2) for decision support in general practice in Denmark.The 13 solutions were aimed at the following disease areas: cancer (n = 5), COPD (n = 3), type 2 diabetes (n = 3), depression (n = 1), liver disease (n = 1), and multiple lifestyle-related diseases (n = 1).Of the 13 solutions, 4 were either developed, tested, or implemented on a national scale and 9 in a limited number of regions or municipalities.As this review did not include an investigation of implementation status beyond what was reported in the identified literature, it was overall not possible to evaluate the current implementation status of the digital solutions as of 2022 (Table 2).Over the course of the inclusion period (2010-2022), there was a progression in the digital solutions as they appeared more complex in recent years.The first study from 2012 described a simple hyperlink solution inserting hyperlinks into electronic test communication [12], whereas the latest study from 2022 described an advanced AI model for the identification of liver disease [26].

Study strengths & limitations
A methodological strength of this rapid review is the use of dual screening to avoid the subjective bias of using a single reviewer.This was applied in both the primary database search and the supplementary search including the snowball search.The dual-screening reduces the risk of missing key material as two reviewers independently reviewed search materials.The snowball search is a methodological strength as it provides a broad overview of the subject area through citation and reference list searches thereby possibly uncovering relevant material that was not identified through the database search.Further, a strength is the inclusion of feasibility and development studies to achieve a thorough understanding of the included digital solutions and preserve an open scope toward novel approaches.Lastly, researchers of various backgrounds contributed to the generation of this paper, which improved the quality of the final work.
A limitation of this review could be the applied definition of decision support.The definition is relatively broad which possibly means that solutions categorized as decision support for this review may not be categorized as such by others.A methodological limitation is that included studies did not undergo quality assessment which may result in variations of study design, sample size, and outcome measures making it difficult to summarize findings.However, as this rapid review did not aim to evaluate intervention effects, a quality assessment was deemed unnecessary [10].Furthermore, it can be discussed if the search in MEDLINE and Embase was sufficient or other databases like PubMed should have been

Purpose Status
Hyperlink in electronic test communication [12] Hyperlink / ICT a Breast cancer 4.870 incident cases per year (mean from years 2016-2020) [34].74.235 prevalent cases at the end of 2019 [34].

Central Denmark Region
To increase access to existing, patient-oriented information about the disease and its treatment via the web for GPs.Online decision support system for Prostate-Specific Antigen (PSA) tests [15] Hyperlink in an electronic medical record system Prostate cancer 4.542 incident cases per year (mean from years 2016-2020) [37].45.610 prevalent cases at the end of 2019 [37].

Central Denmark Region
To aid GPs in deciding if a patient should have a PSA test done, to guide the interpretation of PSA results, or to guide the pathway in a fast-track diagnostic program.
Tested in 114 practices from January 1st 2010 to June 30th 2011 GP reminders on follow-up of abnormal cervical cytology [16] Electronic GP reminder Cervical cancer 342 incident cases per year (mean from years 2016-2020) [38].8.962 prevalent cases at the end of 2019 [38].

Nationwide
To reduce loss to followup in cervical cancer screening

Implemented in 2012
TeleCare North [17,29] Telemonitoring patient data made available to GPs through an electronic monitoring database COPD Prevalence is estimated to 300.000 to 400.000 patients and approximately 14% among individuals aged 35 years and above [36].

North Denmark Region
To improve the management of COPD patients by providing GPs with telemonitoring data on oxygen level, blood pressure, pulse, weight, and symptoms to support GP decision-making.

Implemented in 2012-2014
Electronic Major Depression Inventory (eMDI) [18] Through Web-Patient the eMDI score is automatically returned to the GP's electronic patient record upon filling out from patients

Depression
It is estimated that around 10% of the adult Danish population has depression (estimated on 2013 data) [39].This is equivalent to around 300.000-375.000prevalent cases [40].Table 2 Digital solution characteristics included as well.We do not necessarily believe that this is a methodological limitation to this review as the applied health app filters were developed for and validated in these databases [9], and some search techniques are not supported by PubMed.Additionally, the Cochrane Handbook recommends MEDLINE and Embase as search engines for systematic literature searches [44].However, we do recognize that there might be a difference of opinions about this topic.Another limitation of this rapid review is that it does not include an investigation, beyond the identified literature, of whether the identified digital solutions were ever fully implemented or are still in use as of 2022.[35].Approximately 18.700 incident cases per year [35].

Nationwide
To increase GP prescriptions of lipid-lowering drugs in T2D patients.
The overview was available to Danish GPs in the period from 2011 to 2014.
AI for identification of liver fibrosis patients (LiverAID models) [26] AI algorithm to predict liver stiffness.
Liver fibrosis Approximately 1000 incident cases per year of alcoholic liver cirrhosis and an estimated prevalence of 12-14.000[42].For non-alcoholic fatty liver disease, there is an estimated prevalence of around 1.000.000individuals [43].

Region of Southern Denmark
The LiverAID models could be used for the early detection of patients with asymptomatic chronic liver diseases in primary care.
The LiverAID models were developed with data from patients recruited in the period 2013 to 2020.Not yet tested or implemented in general practice.The potential impact of digital solutions in the healthcare system should be considered.The potential impact will necessarily depend on country setting and the organisational structure of the specific healthcare system.In the Danish example, general practice acts as the gateway to the healthcare system, which means that GPs can refer to patient care at hospitals and specialists.In the Danish GP-setting, digital solutions can aid GPs in decisionmaking in referral for patient care in other segments of the healthcare system by providing a knowledge base or providing prompts/alerts for individuals at potential risk of disease.On one hand, this potential can favour the argument that a strategic goal of improved early detection of disease is realistically achieved as referrals for patient care e.g. at the hospital or at specialist clinics will be supported by an additional knowledge base.On the other hand, it should be considered whether multiple decision support tools could create an information overload that will hamper successful implementation.When implementing digital solutions in the healthcare system it should therefore be carefully considered what the health priorities are in the specific healthcare setting.Continuing the discussion of the potential impact of digital solutions, it should also be addressed whether these tools may contribute to over-or underdiagnosis.Imprecise tools or solutions which do not consider important factors could result in misleading support to healthcare professionals, leading to incorrect or missed diagnosis [45].Additionally, overreliance on digital solutions may lead to overdiagnosis, as the tools identify patients which would not otherwise have sought medical attention and who do not require treatment [46].As such, these potential issues underline the need for these tools to be used only as decision support, in conjunction with the GPs own critical assessment.

Conclusion
In conclusion, this review identified 13 digital solutions for decision support in general practice in a universal healthcare setting in Denmark.The digital solutions covered a range of disease areas (cancer (n = 5), COPD (n = 3), type 2 diabetes (n = 3), depression (n = 1), liver disease (n = 1) and multiple lifestyle-related diseases (n = 1)).Of the 13 solutions, 4 were developed, tested, or implemented on a national scale, and the remaining 9 on a local scale (regional or municipal).The review identified digital solutions with great potential for supporting decision-making in general practice, however, a key learning point is a lack of focus of these studies on how digital solutions are tested, evaluated, and adapted for implementation purposes in general practice.Implementation status could be more transparently reported in publications to enable comparisons across digital solutions and evaluate applicability in general practice.Future studies should consider implementation aspects as part of unfolding the potential of digital solutions as decision support to aid general practitioners in disease detection and management.

Fig. 2
Fig. 2 Flow diagram of the screening process

a:
Information and communication technology

Table 1
Characteristics of key studies Study included 10 observations of preventive health dialogues, 11 interviews with patients, and 7 interviews with GPs.However, it is not stated whether the patients and GPs participating in health dialogues and interviews are the same h: Blood test profiles, consisting of various laboratory analyses